Plant extracts and their components as potential control agents against human head lice

The head lice, Pediculus humanus capitis (Phthiraptera:Pediculidae), is an obligate ectoparasite of humans that causes pediculosis capitis, a nuisance for millions of people worldwide, with high prevalence in children. Pediculosis capitis has been treated by methods that include the physical remotion of lice, various domestic treatments and conventional insecticides. None of these methods render complete protection, and there is clear evidence for the evolution of resistance and cross-resistance to conventional insecticides. Non-toxic alternative options are hence needed for head lice treatment and/or prevention, and natural products from plants, especially essential oils (EOs), are good candidates for safer control agents that may provide good anti-lice activity and low levels of evolved resistance. A few EOs have been tested as repellents with promissory results, although often in vitro tests and clinical trials produce contradictory results. A handful of fixed extracts and several EOs and their individual components have also been tested as contact pediculicides or fumigants. The studies have focused mainly on plant families characterized for the production of EOs. While many EOs and individual compounds showed pediculicide activity, comparing results is difficult due to the diverse bioassay methodologies. Studies of anti-lice activity of individual EO components provide the basis for preliminary conclusions of structure–activity relationships, although no clear patterns can yet be drawn. We here attempt to provide a concise compilation of the available information on anti-lice activity of plant extracts and plant-derived compounds, which we hope may be of help for future developments in this area.

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Determination of the sensitivity of head lice to insecticides]

The author recommends a method of determination of sensitivity of head lice which, in difference from the accepted one, is based on the establishment of the time interval between the death of 50-100% of the insects as a result of the contact with the insecticide in definite doses of the active substance. The method permits to assess the rapidity and the extent of the toxic action of various substances on lice; it is simple and convenient for use in practice.     

Metabolomics to unveil and understand phenotypic diversity between pathogen populations

Leishmaniasis is a debilitating disease caused by the parasite Leishmania. There is extensive clinical polymorphism, including variable responsiveness to treatment. We study Leishmania donovani parasites isolated from visceral leishmaniasis patients in Nepal that responded differently to antimonial treatment due to differing intrinsic drug sensitivity of the parasites. Here, we present a proof-of-principle study in which we applied a metabolomics pipeline specifically developed for L. donovani to characterize the global metabolic differences between antimonial-sensitive and antimonial-resistant L. donovani isolates. Clones of drug-sensitive and drug-resistant parasite isolates from clinical samples were cultured in vitro and harvested for metabolomics analysis. The relative abundance of 340 metabolites was determined by ZIC-HILIC chromatography coupled to LTQ-Orbitrap mass spectrometry. Our measurements cover approximately 20% of the predicted core metabolome of Leishmania and additionally detected a large number of lipids. Drug-sensitive and drug-resistant parasites showed distinct metabolic profiles, and unsupervised clustering and principal component analysis clearly distinguished the two phenotypes. For 100 metabolites, the detected intensity differed more than three-fold between the 2 phenotypes. Many of these were in specific areas of lipid metabolism, suggesting that the membrane composition of the drug-resistant parasites is extensively modified. Untargeted metabolomics has been applied on clinical Leishmania isolates to uncover major metabolic differences between drug-sensitive and drug-resistant isolates. The identified major differences provide novel insights into the mechanisms involved in resistance to antimonial drugs, and facilitate investigations using targeted approaches to unravel the key changes mediating drug resistance.     

Using mechanistic models to understand synchrony in forest insect populations: the North American gypsy moth as a case study

In many forest insects, subpopulations fluctuate concurrently across large geographical areas, a phenomenon known as population synchrony. Because of the large spatial scales involved, empirical tests to identify the causes of synchrony are often impractical. Simple models are, therefore, a useful aid to understanding, but data often seem to contradict model predictions. For instance, chaotic population dynamics and limited dispersal are not uncommon among synchronous forest defoliators, yet both make it difficult to achieve synchrony in simple models. To test whether this discrepancy can be explained by more realistic models, we introduced dispersal and spatially correlated stochasticity into a mechanistic population model for the North American gypsy moth Lymantria dispar. The resulting model shows both chaotic dynamics and spatial synchrony, suggesting that chaos and synchrony can be reconciled by the incorporation of realistic dynamics and spatial structure. By relating alterations in model structure to changes in synchrony levels, we show that the synchrony is due to a combination of spatial covariance in environmental stochasticity and the origins of chaos in our multispecies model.     

Using mathematical models to understand the AIDS epidemic

The most urgent public-health problem today is to devise effective strategies to minimize the destruction caused by the AIDS epidemic. This complex problem will involve medical advances and new public-health and education initiatives. Mathematical models based on the underlying transmission mechanisms of the AIDS virus can help the medical/scientific community understand and anticipate its spread in different populations and evaluate the potential effectiveness of different approaches for bringing the epidemic under control. Before we can use models to predict the future, we must carefully test them against the past spread of the infection and for sensitivity to parameter changes. The long and extremely variable incubation period and the low probability of transmitting the AIDS virus in a single contact imply that population structure and variations in infectivity both play an important role in its spread. The population structure is caused by differences between people in numbers of sexual partners and the use of intravenous drugs and because of the way in which people mix among age, ethnic, and social groups. We use a simplified approach to investigate the effects of variation in incubation periods and infectivity specific to the AIDS virus, and we compare a model of random partner choices with a model in which partners both come from similar behavior groups.     

Using genetics to understand the dynamics of wild primate populations

While much can be learned about primates by means of observation, the slow life history of many primates means that even decades of dedicated effort cannot illuminate long-term evolutionary processes. For example, while the size of a contemporary population can be estimated from field censuses, it is often desirable to know whether a population has been constant or changing in size over a time frame of hundreds or thousands of years. Even the nature of “a population” is open to question, and the extent to which individuals successfully disperse among defined populations is also difficult to estimate by using observational methods alone. Researchers have thus turned to genetic methods to examine the size, structure, and evolutionary histories of primate populations. Many results have been gained by study of sequence variation of maternally inherited mitochondrial DNA, but in recent years researchers have been increasingly focusing on analysis of short, highly variable microsatellite segments in the autosomal genome for a high-resolution view of evolutionary processes involving both sexes. In this review we describe some of the insights thus gained, and discuss the likely impact on this field of new technologies such as high-throughput DNA sequencing.     

Susceptibility of British head lice, Pediculus capitis, to imidacloprid and fipronil

The head louse, Pediculus capitis De Geer (Phthiraptera: Pediculidae) has developed resistance to organochlorines, the organophosphate malathion and to pyrethroids in the U.K. Therefore, headlice from Bristol school children were bioassayed against two new insecticides, fipronil and imidacloprid. Pediculus capitis was fully susceptible to imidacloprid, but it required a relatively high dose and acted slowly. Fipronil acted faster at lower dose, but seemed to be affected by cross-resistance in a small proportion of P. capitis.     

Developmental mechanisms and experimental models to understand forebrain malformative diseases

The development of the central nervous system can be divided into a number of phases, each of which can be subject of genetic or epigenetic alterations that may originate particular developmental disorders. In recent years, much progress has been made in elucidating the molecular and cellular mechanisms by which the vertebrate forebrain develops. Therefore, our understanding of major developmental brain disorders such as cortical malformations and neuronal migration disorders has significantly increased. In this review, we will describe the major stages in forebrain morphogenesis and regionalization, with special emphasis on developmental molecular mechanisms derailing telencephalic development with subsequent damage to cortical function. Because animal models, mainly mouse, have been fundamental for this progress, we will also describe some characteristic mouse models that have been capital to explore these molecular mechanisms of malformative diseases of the human brain. Although most of the genes involved in the regulation of basic developmental processes are conserved among vertebrates, the extrapolation of mouse data to corresponding gene expression and function in humans needs careful individual analysis in each functional system.     

Obese and anorexic yeasts: Experimental models to understand the metabolic syndrome and lipotoxicity

Lipotoxicity is the pathological consequence of lipid overflow in non-adipose tissue, mediated through reactive lipid moieties which may even lead to lipid-induced cell death (lipoapoptosis). This derailment of cellular and organismal fat homeostasis is the consequence of obesity due to continued over-feeding, and contributes substantially to the pathogenesis of insulin resistance, type 2 diabetes mellitus and cardiovascular disease, which are all components of the metabolic syndrome. Now, does yeast, a single-celled eukaryote, ever suffer from the metabolic syndrome and what can we potentially learn from studies in this organism about the underlying molecular mechanism that lead to lipid-associated pathologies in human cells? In this review I will summarize the remarkably conserved metabolic and regulatory processes relevant to establishing cellular energy and lipid homeostasis, as well as recent findings that provide detailed insights into the molecular mechanisms underlying fat-induced cellular malfunction and cell death, with potential implications also for mammalian cells.     

Adhesive models to understand the sensitivity of bio-molecules to environmental signals

Recently, contact mechanics has been widely used to get some understanding of the biological adhesion mechanisms, such as cell-cell adhesion, insects' adhesion and locomotion. JKR theory is usually adopted as a basis, in which the interaction of molecules is considered in contrast to the classical Hertz solution. In this paper, two problems are summarized, which may give some insights to cells or bio-molecules sensitivity to environmental signals: (1) cell reorientation on a stretched substrate; (2) spontaneous detachment between cells or bio-molecules under the variation of environmental signals. The intention here is only to illustrate the possibilities that contact mechanics may explain or predict some bio-phenomena using simple mechanical models. A complete analysis taking into account the full biological complexities is far beyond the scope of this paper. With this objective in mind, the sensitivity of bio-molecules to the environmental signals is described through the variation of adhesive contact area, which is affected by the external forces or deformations. In the first problem, two-dimensional generalized JKR model is used to explain why there exist three stages with two critical values of stretch amplitude controlling cells' reorientation. Three-dimensional adhesive model is used in the second problem, to analyze the spontaneous detachment between two adhering cells or bio-molecules, which may happen at a critical condition.     

Using mathematical models to help understand biological pattern formation

One of the characteristics of biological systems is their ability to produce and sustain spatial and spatio-temporal pattern. Elucidating the underlying mechanisms responsible for this phenomenon has been the goal of much experimental and theoretical research. This paper illustrates this area of research by presenting some of the mathematical models that have been proposed to account for pattern formation in biology and considering their implications.     

Using mathematical models to understand metabolism,genes, and disease

Mathematical models are a useful tool for investigating a large number of questions in metabolism, genetics, and gene–environment interactions. A model based on the underlying biology and biochemistry is a platform for in silico biological experimentation that can reveal the causal chain of events that connect variation in one quantity to variation in another. We discuss how we construct such models, how we have used them to investigate homeostatic mechanisms, gene–environment interactions, and genotype–phenotype mapping, and how they can be used in precision and personalized medicine.